With the advent and proliferation of digital cameras and video recorders, along with increased data storage capabilities at increasingly lower costs, it has become common for users to collect ever increasing numbers of images in a collection. For instance, it is not uncommon for users to take hundreds of digital images during a single event, such as, a wedding, a vacation, and a party. When a user wishes to create a photo album, photobook, or a slideshow containing some of the images, the user typically arranges the photographs in chronological order, based on scene content, or the person who captured the photographs. However, due to the relatively large number of images, users often spend a great deal of time in sorting through the image collection to determine which of the images to include.
Conventional systems for automatic image classification have been applied to multiple images stored in a database. The classification has been used to index images so that the images may be categorized, browsed, and retrieved. In addition, images have been stored in the database with descriptive information regarding the image file, such as, the file creation date, file name, and file extension. Techniques used for image classification are, for the most part, similar to classification techniques applied to any form of digital information.
An exemplary image classification technique provides for navigation through a collection of images to facilitate image retrieval. The appearance of an image is summarized by distribution of color or texture features, and a metric is defined between any two such distributions. A measure of perceptual dissimilarity is provided to assist in image retrieval. Two or three-dimensional Euclidean space has been used to evaluate differences in distances between images to highlight image dissimilarities. The results may be used to assist in a database query for locating a particular image.